A study on volatility and large-cap stocks

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Category: 
Industry

Introduction

One of the main arguments at Thaistocks.com is that the SET is
wrongly regarded as a gamblers den for those who enjoy trading in
highly speculative stocks. For years, Paul Renaud has been
unearthing hidden gems that go along the theme of high dividends,
promising growth and low volatility. Frequently, these stocks
were small- to mid-sized cap stocks that institutional investors
and the media ignored due to the lack of liquidity to suit their
needs. This so-called lack of liquidity did not prevent regular
investors from investing and cashing in with remarkable gains.
With his 15 years of investment experience in Thailand Paul
noticed a trend: The most speculative stocks o­n the SET
tend to be the largest capitalized companies within their
respective sector. The following mini-study attempts to prove
this assertion by analyzing the average 3-year betas of large
caps and comparing them to the average beta of their sector.

Beta Primer

The beta coefficient is defined as the amount of systematic
(or market risk) present in a stock relative to the average
amount of risk present in all stocks (in this case the SET). The
average amount of systematic risk in all stocks has a beta of
1.0. A stock with a beta of 0.50 will have half the amount of
systematic risk compared to the average, and a stock with a beta
of 2.0 will have twice the amount of risk present. The premise is
that the higher the beta for a stock, the higher the
volatility.

Methodology

Using data prepared by TISCO Securities, Thaistocks.com
obtained 3-year betas for all companies listed o­n the SET.
The 3-year betas were calculated in the last quarter of 2003. The
twelve largest sectors, representing 88% of the SET index, were
then chosen to be analyzed. Companies that had halted trading but
still listed were eliminated from the study. Companies that had
recent IPOs were included in the study. The average 3-year beta
was then calculated for each sector. Next, the largest companies
in each sector were chosen. This was done qualitatively, which
resulted in 2 to 5 large caps being selected in each sector. The
average beta was then calculated for the large caps in each
sector, and then compared to the sector average beta.

Results

The results are summarized in the table below. The assertion
that the larger cap stocks are more risky relative to other
stocks in their sector was proven true in 10 out of the 12
sectors analyzed. The two sectors in which the assertion was not
true were the Communications and Energy sectors. The average
large cap stock had a larger beta by 0.24 than the average beta
of stocks in its sector.

Sector

% of SET Index

Avg. Beta

Avg. Beta Large Caps

Difference

Energy

16.7

0.9270

0.8760

-0.0510

Banking

13.84

1.1692

1.3125

0.1433

Building

11.24

0.9523

1.0525

0.1002

Comunications

10.23

1.3267

1.1050

-0.2217

Property

9.31

1.0476

1.4100

0.3624

Chemicals

4.83

0.7142

1.7867

1.0725

Rehabilitation

4.79

0.5948

0.8267

0.2319

Finance

4.18

1.3172

1.9225

0.6053

Transportation

4.1

0.9714

1.1050

0.1336

Entertainment

3.26

0.8100

0.9767

0.1667

Commerce

2.83

0.4153

0.6100

0.1947

Agribusiness

1.45

0.4057

0.5350

0.1293

Average Difference:

0.2389

Interpretation

The average difference of 0.24 represents a significant
amount of increased systematic risk for the large-cap stocks.

This tells investors that when analyzing a sector and choosing
companies within the sector that bigger is not always better.
Please also refer to Paul Renaud’s recent article:
A blue chip stock is not necessarily a blue chip in
Thailand.
The combined increased risk of larger-caps
along with the facts of low-dividend yields and poor performance
over the past several years does not result in an encouraging
outlook for the larger-caps.

This goes along with the investment strategy that
Thaistocks.com has followed over the years of focusing o­n
medium sized companies and adding a select few large caps to
balance the portfolio, while at the same time keeping a close eye
o­n volatility.